A deep learning architecture for power management in smart cities-Reference-Cited by-同舟云学术

A deep learning architecture for power management in smart cities

Published:2022-11 Issue: Volume:8 Page:1568-1577
ISSN:2352-4847
Container-title:Energy Reports
language:en
Short-container-title:Energy Reports

Author:

Xin Qin,Alazab Mamoun,Díaz Vicente García,Montenegro-Marin Carlos Enrique,Crespo Rubén González

Publisher

Elsevier BV

Subject

General Energy

Reference32 articles.

1. IoT isan operating system-based fuzzy inference system for home energy management systems in smart buildings;Ain;Sensors,2018

2. Privacy-aware energy-efficient framework using the internet of medical things for COVID-19;Al-Turjman;IEEE Internet Things Mag.,2020

3. Multi-objective cluster head selection using fitness averaged rider optimization algorithm for IoT networks in smart cities;Alazab;Sustain. Energy Technol. Assess.,2021

4. Multi-objective cluster head selection using fitness averaged rider optimization algorithm for IoT networks in smart cities;Alazab;Sustain. Energy Technol. Assess.,2021

5. Energy management in harvesting enabled sensing nodes: Prediction and control;Ashraf;J. Netw. Comput. Appl.,2019

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